Defining the boundaries and area of the Samarkand Reservoir catchment based on digital elevation models

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DOI:

https://doi.org/10.26577/JGEM.2021.v62.i3.03
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Abstract

This article discusses a low-cost approach for delineating the boundaries and area of the catchment, applicable for designing new and monitoring the state of existing hydrotechnical structures on the example of the Samarkand reservoir in the Karaganda region of the Republic of Kazakhstan. The idea of the study is to apply hydrological tools of geoinformation systems (GIS) and open data of digital elevation model (DEM) in order to promptly obtain maps of surface runoff in vector and raster formats. Such maps can be used by hydrological engineers to calculate surface water discharge and, in combination with a soil map, groundwater discharge. To produce quality maps, the study tested DEMs from various open source, commercial, and open-source software; ArcGIS software tools such as Mosaic To New Raster, Fill Sinks, Flow Direction, Flow Accumulation, Raster to Polygon, and Clip were used. Based on the results of the study, the most suitable DEMs with a resolution of 10 m per pixel and covering the entire potential territory of the study catchment were downloaded from the Internet resource OpenTopography. The DEM processing made it possible to obtain a fairly accurate outline of the catchment boundaries in vector format, as well as maps of surface runoff and elevations in raster format. The total area and length of the catchment boundaries, were 228777 km2 and 1118 km respectively. As the study continues, the maps obtained will be used to develop a hydrological model and an improved approach to dam design and monitoring in river basins subjected to urbanization. The approach proposed in the study can be improved when using DEMs with a resolution below 10 m.

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Published

2021-10-19

How to Cite

Aldungarova, A., Utepov, Y., Mkilima, T., Tulebekova, A., Zharassov, S., & Abisheva, A. (2021). Defining the boundaries and area of the Samarkand Reservoir catchment based on digital elevation models . Journal of Geography and Environmental Management, 62(3), 32–42. https://doi.org/10.26577/JGEM.2021.v62.i3.03